ArticleThe journal of prevention of Alzheimer's disease2023
Predicting Progression from Normal to MCI and from MCI to AD Using Clinical Variables in the National Alzheimer's Coordinating Center Uniform Data Set Version 3: Application of Machine Learning Models and a Probability Calculator.
Article in The journal of prevention of Alzheimer's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Limited generalizability and high risk of bias in multivariable models predicting conversion risk from mild cognitive impairment to dementia: A systematic review.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Pooled it
- Deep survival modeling to predict future cognitive impairment in unimpaired adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Mild cognitive impairment-to-Alzheimer's dementia progression risk: the contribution of the Interceptor project.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Resource-stratified machine learning framework for cognitive status classification and mild cognitive impairment to dementia progression prediction.Alzheimer's research & therapy · 2026Article
- Linking sleep apnea and arthritis in the National Alzheimer Coordinating Center Cohort: A cross-sectional analysis.Medicine · 2026Article
- Stratifying dementia risk factors: A prediction model and hypothesis-driven analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Neurotechnological Approaches to Cognitive Rehabilitation in Mild Cognitive Impairment: A Systematic Review of Neuromodulation, EEG, Virtual Reality, and Emerging AI Applications.Brain sciences · 2025Review
- AI-powered FDG-PET radiomics: a door to better Alzheimer's disease classification?European radiology · 2025Article
- Joint ensemble learning-based risk prediction of Alzheimer's disease among mild cognitive impairment patients.The journal of prevention of Alzheimer's disease · 2025Article
- Federated learning with multi-cohort real-world data for predicting the progression from mild cognitive impairment to Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Inequalities in Mild Cognitive Impairment Risk Among Chinese Middle-Aged and Older Adults: Insights from an Integrated Learning Model.Risk management and healthcare policy · 2025Article
- Conversion to Alzheimer's disease dementia from normal cognition directly or with the intermediate mild cognitive impairment stage.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Predicting Progression From Mild Cognitive Impairment to Alzheimer's Dementia With Adversarial Attacks.IEEE journal of biomedical and health informatics · 2024Article
- MC-ViViT: Multi-branch Classifier-ViViT to Detect Mild Cognitive Impairment in Older Adults Using Facial Videos.Expert systems with applications · 2024Article
- An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer's Disease Using UK Biobank.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Optimizing Machine Learning Models for Accessible Early Cognitive Impairment Prediction: A Novel Cost-effective Model Selection Algorithm.IEEE access : practical innovations, open solutions · 2024Article
- Predicting Conversion Time from Mild Cognitive Impairment to Dementia with Interval-Censored Models.Journal of Alzheimer's disease : JAD · 2024Article
- Employing Deep-Learning Approach for the Early Detection of Mild Cognitive Impairment Transitions through the Analysis of Digital Biomarkers.Sensors (Basel, Switzerland) · 2023Article
- Predictive power of gait and gait-related cognitive measures in amnestic mild cognitive impairment: a machine learning analysis.Frontiers in human neuroscience · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Clinical trials are increasingly focused on pre-manifest and early Alzheimer's disease (AD). Accurately predicting clinical progressions from normal to MCI or from MCI to dementia/AD versus non-progression is challenging. Accurate identification of symptomatic progressors is important to avoid unnecessary treatment and improve trial efficiency. Due to large inter-individual variability, biomarker positivity and comorbidity information are often insufficient to identify those destined to have symptomatic progressions. Using only clinical variables, we aimed to predict clinical progressions, estimating probabilities of progressions with a small set of variables selected by machine learning approaches. This work updates our previous work that was applied to the National Alzheimer's Coordinating Center (NACC) Uniform Data Set Version 2 (V2), by using the most recent version (V3) with additional analyses. We generated a user-friendly conversion probability calculator which can be used for effectively pre-screening trial participants.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.